Financial services: taking AI to the next level

Produced by

Parts of the financial sector, notably wealth management and equity trading, have been among the first movers in the commercial use of AI. The scope of AI-led innovation is now widening: banks and insurers are actively applying AI techniques in the front and back office, developing innovative customer-facing services and automating operations such as payments, risk modelling and fraud detection.

One of the key drivers for such swift adoption of AI in the financial industry is cost savings. By 2030, traditional finance sector organisations could reduce their costs by 22%, according to fintech research company Autonomous Research, in what would amount to more than $1 trillion in efficiencies. These savings would come from the front, middle and back office operations and includes a reduction is retail branches and bank tellers, the application of AI to compliance and data processing, and the automation of underwriting and collections systems.

Outside of the financial motivations, technology companies—notably small fintechs—have provided the impetus for much of the innovation itself. Some established financial sector players have responded energetically themselves, co-opting fintechs’ AI expertise and innovations. But Andrei Kirilenko of Imperial College London maintains that the variety of services traditional banks and insurers offered remains limited. He expects a new wave of innovation as technology companies exert more pressure on the industry to meet customer demand for smarter, more personalised products. “New financial products that no one heard of before will proliferate,” he says.

More data, better predictions, faster service

What directions will AI-led innovation take? One will be marked improvement in capabilities that exist today, as machine learning tools analyse ever larger amounts of data in ever wider varieties. For example, equity trading algorithms used by investment management firms and hedge funds should gain in predictive accuracy, something which has considerable room for improvement, according to some analysts.

Market strategy and potential targets

According to William Genovese, Vice President of Corporate Strategy Planning, Banking and Financial Markets at technology company Huawei, one very popular use case will be robo advisors for investments. “I believe that target markets should be centered around two customer segments to optimally get the job done,” he says. This would see robo-advisors used at the lower end while marketing to new investors who would welcome robo-advisory as a self-service tool for its simplicity and flexibility. In most emerging markets, the rising number of middle class and upper middle class consumers are looking for opportunities to invest. However, the lack of knowledge and access to information prevent them from investing. For the lower end disruption of the market, simplicity is the defining character. The design of robo-advisors should initially be simple and easy to understand by the investors. Basic applications that are publicly available in the market like Bloom, Robinhood, Stash, and Acorns serve the investors’ need and demand in the lower end market. For instance, Stash offers fund investments based on lifestyle preferences and interests—for example, clean water technology companies, internet companies. These applications are straightforward and simple to use and readily adaptable and consumable by these new customers. “Due to these features, investors can quickly learn how to invest and they can test the markets based on their life interests and causes by investing in a collection of companies that reflect their desires and goal accordingly,” Mr Genovese adds.

The chatbots that banks are now using for customer interaction will similarly use wider data access and continuous learning to make more targeted offers to customers and provide more accurate remedies to resolve issues. In five years, such virtual assistants may rival websites and the physical branch in importance as banking channels for customers. In a global survey conducted by The Economist Intelligence Unit in early 2018, banking executives pointed to “improvement of the customer experience” and “greater customer engagement” as the main benefits their firms will generate from AI use in the next five years.

Robo-advisors, algorithm-driven tools used by wealth management firms to provide automated financial planning services to customers, were among the earliest manifestations of AI in the financial sector. They continue to gain in sophistication and still have considerable room for growth. According to one source, robo-advisors will manage $1 trillion in assets by 2020 and close to $4.6 trillion by 2022. That figure is around $200 billion today.

Cross-sector germination

New payment models and services are likely to emerge as financial service providers gain wider access to data from other sectors. The insurance industry’s access to automotive data, generated by in-car IoT sensors, is leading to the growth of usage-based car insurance, for example, in which AI-based assessments of driver behaviour factor into “pay-how-you-drive” premiums.

Dr Kirilenko similarly expects the ability of insurers and banks to apply AI techniques to the analysis of customers’ health data—generated, for example, from personal health monitoring devices—to result in new types of financial products. Wealth managers will also craft investment products and advice to fit customers’ health profiles. Stricter data privacy rules in some markets may impede such sharing of such data in the short term, but cross-sector data flows will inevitably increase, he believes, as customers come to expect more joined-up financial, health and other lifestyle products.

Disruption to come

There will also be change, believes Dr Kirilenko, in the mix of players able to offer financial services. Combining their AI and broader digital expertise with their unique ability to glean customer behaviour and preferences, large technology companies will come to compete more directly with traditional financial institutions. “Regulators in many markets are more open today to the idea of replacing parts of the financial systems with technologies that work,” he says.

Action required

The uses of AI detailed above require that firms have access to ever greater amounts of computing capacity to support the more powerful algorithms they will run. Banks and insurers have been less avid users of public cloud services than firms in other industries, due partly to perceived risks to customer and proprietary data. That is likely to change as cloud service providers assuage security concerns, and as banks and insurers become more active partners with fintechs and other organisations—including even competitors—in innovation-oriented ecosystems. Many companies will find that they cannot take their AI initiatives to the desired scale without greater use of the cloud.

The admonition that organisations’ data assets must be readied for AI uses applies to all industries, but the challenge may be greater for established financial industry players. For example, research conducted by the consultancy PwC in early 2018 found that financial services firms were among the least effective in their use of data in a cross-sector comparison. Only 26% of financial sector executives said their firms use data effectively, third lowest of ten industries covered. There is much to do to redress this, but industry firms will need to integrate as many siloed data sets and systems as regulation allows, as to be effective AI needs access to wide varieties of data, and in different formats. Banks and insurers both will also need to deploy analytics tools that are adept at working with unstructured data.

This is not entirely uncharted territory for established financial industry players, and many are moving ahead aggressively to build AI capabilities. But if the borders separating the financial and other sectors erode as Dr Kirilenko predicts, many financial institutions will find it difficult to keep pace.

HUAWEI CONNECT 2018 – “Activate Intelligence” – will be held at the Shanghai World Expo Exhibition and Convention Center and Expo Center from October 10 to 12.

This year’s HUAWEI CONNECT conference is designed to help all businesses and organizations step over the threshold and stake their claim in the intelligent world. You will be joined by the best minds in the industry – including global ICT leaders, industry experts, and ecosystem partners – to chart the way forward and explore new opportunities.

Huawei is a leading global provider of information and communications technology (ICT) infrastructure and smart devices. With integrated solutions across four key domains – telecom networks, IT, smart devices, and cloud services – we are committed to bringing digital to every person, home and organization for a fully connected, intelligent world. Huawei’s end-to-end portfolio of products, solutions and services are both competitive and secure. Through open collaboration with ecosystem partners, we create lasting value for our customers, working to empower people, enrich home life, and inspire innovation in organizations of all shapes and sizes. At Huawei, innovation focuses on customer needs. We invest heavily in basic research, concentrating on technological breakthroughs that drive the world forward. We have more than 180,000 employees, and we operate in more than 170 countries and regions. Founded in 1987, Huawei is a private company fully owned by its employees.

Produced by (E) BrandConnect, a commercial division of The Economist Group, which operates separately from the editorial staffs of The Economist and The Economist Intelligence Unit. Neither (E) BrandConnect nor its affiliates accept any responsibility or liability for reliance by any party on this content.